ITMANET FLoWS Focus Talk

Interference in MANETs: Friend or Foe?

Andrea Goldsmith

Joint work with Dabora, Gunduz, Kramer, Liu, Maric, Poor, Shamai

MANET Characteristics

Peer-to-peer communications All transmissions interfere due to broadcast

nature of radio Highly dynamic Nodes can cooperate to forward data Can introduce feedback to improve

performance

Interference in MANETs Radio is a broadcast medium

Radios in the same spectrum interfere

MANET capacity in unknown for all canonical networks with interference (even when exploited)Z ChannelInterference ChannelRelay ChannelGeneral MANETs

Interference: Friend or Foe?

If treated as noise: Foe

If decodable or precodable: Neutral Neither friend nor foe

IN

PSNR

Increases BER,

Reduces capacity

Multiuser detecion (MUD) and precoding

can completely remove interferenceCommon coding strategy to

approach capacity

If exploited via coding, cooperation, and

cognition

Friend

Interference: Friend or Foe?

Especially in a network setting

Exploiting Interference through

Coding

Capacity of Z channel unknown in general

We obtain capacity for a class of Z channels• Korner/Marton technique applicable• Enough to consider superposition

encoding• Han/Kobayashi achievable region is

capacity region

Yields capacity for large class of Gaussian interference channels

The Z Channel

Exploiting Interference through

Cognition

Cognitive user has knowledge of other user’s message and/or encoding strategyUsed to help noncognitive

transmissionUsed to presubtract noncognitive

interferenceRX1

RX2NCR

CR

Joint with Maric, Kramer, Shamai

8

Proposed Transmission Strategy

Rate splitting

Precoding againstinterference

at CR TX

Cooperationat CR TXCooperation

atCR TX

Coop

era

tion

at

CR

TX P

reco

din

g a

gain

stin

terfe

ren

ceat C

R T

X

To allow each receiver to decode part of the other node’s message

reduces interference

Removes the NCR interference at the CR RX

To help in sending NCR’s

message to its RX

We optimally combine these approaches into

one strategy

More Precisely: Transmission for Achievable Rates

Rate split

(.)1cUP

NCR

)|(. 1| 11 cUU uPca

2W(.)

2XPNX2

1W cW

aW1

N

cU

1

NX2

NX2

NN

acUU

11,

NX2

NX1

2W

CR

The NCR uses single-user encoder

The CR uses - Rate-splitting to allow receiver 2 to decode part of cognitive user’s message and thus reduce interference at that receiver - Precoding while treating the codebook for user 2 as interference to improve rate to its own receiver - Cooperation to increase rate to receiver 2

RX1

RX2NCR

CR

10

Upper Bounds

How far are the achievable rates from the outer bound?

• Follows from standard approach: • Invoke Fano’s inequality

• Reduces to outer bound for full cooperation for R2=0

• Has to be evaluated for specific channels

Performance Gains from Cognitive

Encoding

CRbroadcast

bound

outer bound

our schemeprior schemes

Exploiting Interference through Relaying

Relaying strategies: Relay can forward all or part of the

messages Much room for innovation

Relay can forward interference To help subtract it out

TX1

TX2

relay

RX2

RX1X1

X2

Y3=X1+X2+Z3

Y4=X1+X2+X3+Z4

Y5=X1+X2+X3+Z5

X3= f(Y3)

Joint with Maric, Dabora, Medard

Achievable Rates withInterference Forwarding

)|;(

);,,(

);,,(

)|;,(

),|;(

3322

232121

132121

12322

32111

XYXIR

YXXXIRR

YXXXIRR

XYXXIR

XXYXIR

• The strategy to achieve these rates is:

- Single-user encoding at the encoder 1 to send W1

- Decode/forward at encoder 2 and the relay to send message W2

• This region equals the capacity region when the interference is strong and the channel is degraded

for any distribution p(p(x1)p(x2,x3)p(y1,y2|x1,x2,x3)

dest1

dest2

encoder 1

encoder 2

relay

Capacity Gains fromInterference Forwarding

Diversity-Multiplexing Tradeoffs in

Multi-Antenna MANETs

iiii

i WXHM

SNRY

• Focus on (M1, M2, M3)

• Quasi-static Rayleigh fading channel

• Channel state known only at the receivers

Joint with Gunduz, Poor

- Multiplexing gain r: - Diversity gain d

Diversity-Multiplexing Tradeoff in

Point-to-Point MIMO Channels

))(()( 2121kMkMkd MM

DMT for Full-duplex Relays

The relay can receive and transmit simultaneously

The DMT for (M1,M2,M3) full-duplex system is

The hop with the minimum diversity gain is the bottleneck

Achieved by decode-and-forward relaying with block Markov structure

Follows easily since DF achieves capacity

)}(),(min{)(3221321

rdrdrd MMMMMMM

Half-duplex Relay

Static Protocols: The source transmits during the first aT channel

uses, 0<a<1The relay tries to decode the message and forwards over the remaining (1-a)T channel uses:

decode-and-forward with fixed allocation (fDF)

The DMT for half-duplex (M1,M2,M3) system with fixed time allocation a

Optimize a for each multiplexing gain: decode-and-forward with variable

allocation (vDF)

a

rd

a

rdrd MMMM

fDF

MMM 1,min)(

3221321

Dynamic Decode-and-Forward (DDF) for Half-duplex Relay

Introduced by Azarian et al. (IT’05): Relay listens until decoding Transmits only after decoding

Achieves the best known DMT for half-duplex relay channels, yet short of the upper bound

We show: Achieves optimal DMT in multi-hop relay channels

Not piece-wise linear, no general closed form expression

Can be cast into a convex optimization problem

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10

0.5

1

1.5

2

2.5

3

3.5

4

Multiplexing gain, (r)

Div

ers

ity g

ain

, d(r

)

DMT of (4,1,3) half-duplex relay channel

d4,1

(r)

d1,3

(r)

dDDF

(r)

dvDF

(r)

dfDF

(r), a=0.5

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20

0.5

1

1.5

2

2.5

3

3.5

4

Multiplexing gain, (r)

Div

ers

ity g

ain

, d(r

)DMT of (2,2,2) half-duplex relay channel

d2,2

(r)

dDDF

(r)

dvDF

(r)

• Multiple full-duplex relays: • DMT dominated by hop with minimum diversity gain.

• Multiple half-duplex relays: • Odd and even numbered relays transmit in turn. • DDF (with time limitation for successive hops) is DMT optimal.• DMT dominated by 2 consecutive hops with min. diversity gain

Multiple Relay Networks

End to End DistortionUse antennas for multiplexing:

Use antennas for diversity

High-RateQuantizer

ST CodeHigh Rate Decoder

Low-RateQuantizer

ST CodeHigh

DiversityDecoder

0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 20

0.5

1

1.5

2

2.5

3

3.5

4

Multiplexing gain, (r)

Div

ers

ity g

ain

, d(r

)

DMT of (2,2,2) half-duplex relay channel

d2,2

(r)

dDDF

(r)

dvDF

(r)

We optimize the point on the DMT tradeoff curve to minimize distortion

Exploiting Interference reduces

End-to-End Distortion

Interference exploitation at the physical layer improves end-to-end distortion

We have proved a separation theorem for a class of interference channelsSeparate source and channel

coding optimal

We found the operating point on the DMT multihop region for minimal distortionUnder delay constraints,

optimization needed

Summary Fundamental performance limits of

MANETS requires understanding and exploiting interference

Interference can be exploited via coding/relaying, cooperation, or cognitionThe right strategy depends on CSI,

dynamics, network topology, and node capabilities.

Exploiting interference leads to higher capacity, more robustness, and better end-to-end performance

MIMO adds a new degree of freedom at each nodeUse antennas for multiplexing, diversity, or

IC?

Final Comments: Startup Lessons

Learned People in industry read our papers and

implement our ideas• Communication and network theory can be

implemented in a real system in 3-9 months

• Information Theory heavily influences current and next-gen. wireless systems (mainly at the PHY & MAC layers)• Idealized assumptions have been

liberating• Wireless network design above PHY/MAC layer is ad-hoc

• The most effective way to do tech transfer is to start a company